Ben Bernanke Quotes

Data, I think, is one of the most powerful mechanisms for telling stories. I take a huge pile of data and I try to get it to tell stories.

The problem with data is that it says a lot, but it also says nothing. 'Big data' is terrific, but it's usually thin. To understand why something is happening, we have to engage in both forensics and guess work.

The greatest moments are those when you see the result pop up in a graph or in your statistics analysis - that moment you realise you know something no one else does and you get the pleasure of thinking about how to tell them.

Information is expanding daily. How to get it out visually is important.

Personally, I find visualisations great for helping me understand the world and for sifting the huge amounts of information that deluge me every day.

There is a rampant tendency in any industry where someone is trying to sell something with a bunch of data, where they cherry pick a little bit... bias a little bit. This becomes quite easy when there is an enormous amount of data to cherry pick from.

Here's the thing: If you're monitoring every single thing that goes on in a given culture, if you have all the information that is there to be had, then that is the equivalent of having none of it. How are you going to process that amount of information?

What I love - and I'm a journalist - and what I love is finding hidden patterns; I love being a data detective.

We're rapidly entering a world where everything can be monitored and measured. But the big problem is going to be the ability of humans to use, analyze and make sense of the data.

There's something that happens with the collection of a large amount of data when it's dumped into an Excel spreadsheet or put into a pie chart. You run the risk of completely missing what it's about.

Social media has given companies access to unprecedented amounts of information on client behavior and preferences - so-called Big Data. But making sense of it all and turning it into actionable policy has been elusive.

In China, Internet surveillance has already become a profitable industry. In fact, a growing number of private firms eagerly assist the local police by aggregating this data and presenting it in easy-to-browse formats, allowing humans to pursue more analytical tasks.

There's a lot of power in executing data - generating data and executing data.

I have more information in one place than anybody in the world.

Go out and collect data and, instead of having the answer, just look at the data and see if the data tells you anything. When we're allowed to do this with companies, it's almost magical.

Rob Engle and I are concerned with extracting useful implications from economic data, and so the properties of the data are of particular importance.

We have entered an era where the kinds of data and analyses that people run have gotten incredibly complicated. So you have researchers using sophisticated software programs that they probably don't understand but are generally accepted and everyone [in the field] uses.

Good data is hard to find. Hard data is good to find.

Collect it all!

The job of the data scientist is to ask the right questions.

People believe the best way to learn from the data is to have a hypothesis and then go check it, but the data is so complex that someone who is working with a data set will not know the most significant things to ask. That's a huge problem.

For me myself, I feel it's always interesting gathering data. I have my team who do that. I think they feed me through specific things that I might find valuable.

My job is to analyze our data set to understand it and build products on it. I look at raw data, do the math to clean it up, and build systems to make it easy to understand.

The big mystery of Big Data is causation versus correlation.

If we just focus on stats, we're gonna eventually not have them.